Key Takeaways:
- Chase Markel, a University of Wyoming Ph.D. student, is developing an AI model to predict the risk of congestive heart failure in cattle based on images of a cow’s heart.
- The model has achieved a 92% accuracy rate in assigning the correct score to images it has never encountered before.
- Markel’s research aims to alleviate financial losses associated with congestive heart failure in the cattle industry.
- The AI model has the potential to revolutionize the field of animal science and improve the bottom line for producers.
- Markel is also developing a similar model to evaluate liver images for the presence and severity of liver abscesses in feedlot cattle.
Introduction to Chase Markel’s Research
Chase Markel, a University of Wyoming Ph.D. student from Wheatland, is harnessing artificial intelligence to transform how animal scientists study risk factors for congestive heart failure in cattle. Markel’s AI model, the first of its kind, has been trained to predict the risk of congestive heart failure based on images of a cow’s heart. As Markel notes, "I’m not a computer scientist, I’m not an AI guy. I’m someone who is studying heart failure [in cattle] and just happened to have the right conversation and made the connection in order to build something that I think can be useful." Markel’s research is a prime example of how emerging technologies can be leveraged to address some of the most pressing challenges in the cattle industry.
Background and Motivation
Markel’s interest in this area of research stems from his background in the cattle industry. He completed both his undergraduate and master’s degrees in the UW Department of Animal Science and is currently pursuing a doctorate in the same department. As a master’s student, Markel studied pulmonary hypertension, also known as high-altitude disease or brisket disease, in cattle. He found that subclinical cases of pulmonary hypertension may have larger economic impacts than direct profit losses incurred when an animal dies before harvest. This research led him to investigate the link between pulmonary hypertension and congestive heart failure, which is the focus of his doctoral research. As Markel explains, "Anything we can do to improve traceability and individual animal identification back as far as we can go in the production cycle to try to prevent these things is a net benefit for the industry."
The AI Model
Markel’s AI model is a computer vision model that has been trained on thousands of heart images taken in commercial processing plants in Nebraska and Colorado. The model uses a 1-5 scoring system developed by Tim Holt, a professor at Colorado State University, to categorize images by score. To date, Markel’s dataset includes nearly 7,000 images, each of them scored by hand, then used to train the model. The new tool has already achieved a startling degree of accuracy, with the AI model assigning the correct score 92% of the time. As Markel notes, "As researchers, we need to start incorporating these tools into our research and…build that technology so producers and people out in the industry can actually utilize those tools and help improve their bottom line."
Potential Applications and Impact
Markel’s research has the potential to revolutionize the field of animal science and improve the bottom line for producers. The AI model can be used to identify economically relevant risk factors in individual animals, which can help producers make informed decisions about their herds. While Markel’s current models are best suited for application in processing plants, he hopes that future iterations will benefit Wyoming producers more directly. As Kelly Crane, Farm Credit Services of America dean in the College of Agriculture, Life Sciences and Natural Resources, comments, "Chase Markel’s research exemplifies our college’s commitment to conducting Wyoming-relevant research, which integrates emerging technologies, producer experiences and UW faculty expertise to address some of Wyoming agriculture’s most vexing challenges."
Future Developments and Patent Application
Markel is currently developing a similar model to evaluate liver images for the presence and severity of liver abscesses, another common affliction in feedlot cattle. He has also submitted a provisional patent application to the U.S. Patent and Trademark Office (USPTO) through UW and hopes to obtain full patent protection in 2026. As Markel continues to refine his model and explore new applications, his research is likely to have a significant impact on the cattle industry. For questions about Markel’s research, he can be contacted at protected email.
UW Student Develops Artificial Intelligence Model to Study Heart Failure in Cattle